Individual and organizational predictors of health care aide job satisfaction in long term care
Bibliographic record
Abstract
BACKGROUND: Unregulated health care aides provide the majority of direct health care to residents in long term care homes. Lower job satisfaction as reported by care aides is associated with increased turnover of staff. Turnover leads to inferior job performance and negatively impacts quality of care for residents. This study aimed to determine the individual and organizational variables associated with job satisfaction in care aides. METHODS: We surveyed a sample of 1224 care aides from 30 long term care homes in three Western Canadian provinces. The care aides reported their job satisfaction and their perception of the work environment. We used a hierarchical, mixed-effects ordered logistic regression to model the relative odds of care aide job satisfaction for individual, care unit, and facility factors. RESULTS: Care aide exhaustion, professional efficacy, and cynicism were associated with job satisfaction. Factors in the organizational context that are associated with increased care aide job satisfaction include: leadership, culture, social capital, organizational slack-staff, organizational slack-space, and organizational slack-time. CONCLUSIONS: Our findings suggest that organizational factors account for a greater increase in care aide job satisfaction than do individual factors. These features of the work environment are modifiable and predict care aide job satisfaction. Efforts to improve care aide work environment and quality of care should focus on organizational context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".